x

langchain_benchmarks/tool_usage/agents/base.py

@@ -0,0 +1,11 @@
+import abc
+
+from langchain_core.runnables import Runnable
+
+
+class AgentFactory(abc.ABC):
+    """Abstract class for agent factory"""
+
+    @abc.abstractmethod
+    def __call__(self) -> Runnable:
+        """Create a new agent"""

langchain_benchmarks/tool_usage/agents/runnable_agent.py

@@ -10,9 +10,10 @@
 
 from langchain_benchmarks.schema import ToolUsageTask
 from langchain_benchmarks.tool_usage.agents.adapters import apply_agent_executor_adapter
+from langchain_benchmarks.tool_usage.agents.base import AgentFactory
 
 
-class CustomRunnableAgentFactory:
+class CustomRunnableAgentFactory(AgentFactory):
     """A factory for creating tool using agents.
 
     A factory for agents that do not leverage any special JSON mode for

langchain_benchmarks/tool_usage/agents/tool_using_agent.py

@@ -12,9 +12,10 @@
 from langchain_benchmarks.rate_limiting import RateLimiter, with_rate_limit
 from langchain_benchmarks.schema import ToolUsageTask
 from langchain_benchmarks.tool_usage.agents.adapters import apply_agent_executor_adapter
+from langchain_benchmarks.tool_usage.agents.base import AgentFactory
 
 
-class StandardAgentFactory:
+class StandardAgentFactory(AgentFactory):
     """A standard agent factory.
 
     Use this factory with chat models that support the standard LangChain tool

tests/unit_tests/tool_usage/test_public_api.py

@@ -6,5 +6,11 @@ def test_public_api() -> None:
     # This test will also fail if __all__ is not sorted.
     # Please keep it sorted!
     assert __all__ == sorted(
-        ["apply_agent_executor_adapter", "get_eval_config"], key=str.lower
+        [
+            "apply_agent_executor_adapter",
+            "get_eval_config",
+            "CustomRunnableAgentFactory",
+            "StandardAgentFactory",
+        ],
+        key=str.lower,
     )